Using AHP to measure the perception gap between current and potential users of bus services

Mahmoud, Moataz; Hine, Julian

doi:10.1080/03081060.2012.745316

Cited by 73 publications

(29 citation statements)

References 28 publications

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“…Accordingly, LCCs can ensure long-term success by responding to the determinants of customer purchase intentions. Mahmoud and Hine (2013) also argued that potential and current customers of transportation services have different amounts of information and use different criteria for making purchase decisions. For LCCs, both initial sales to potential customers and repeat sales to current customers are critical for survival and long-term profitability.…”

Section: Introductionmentioning

confidence: 98%

Using analytic network process to measure the determinants of low cost carriers purchase intentions: A comparison of potential and current customers

Lin

Huang

2015

Journal of Air Transport Management

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Section: Introductionmentioning

confidence: 98%

Using analytic network process to measure the determinants of low cost carriers purchase intentions: A comparison of potential and current customers

Lin

Huang

2015

Journal of Air Transport Management

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“…Iseki and Taylor (2010) used an Importance-Satisfaction (I-S) analysis to identify the attributes passengers found most important, based on their collective in-the-moment perceptions, surveyed at a number of transit stops, whereas Tyrinopoulos and Antoniou (2008) measured the variability of the users'perceived satisfaction on different service levels using an ordered probit model. The second approach is the 'weighted perception measure' that analyses the importance of different service attributes on users' overall perception of service quality (Mahmoud and Hine 2013). In this approach, a number of statistical techniques have been used by researchers, like structural equation modelling Mazzulla 2007, 2012;de Ona et al 2013), quadrant analysis (Martilla and James 1977), factor analysis (Tyrinopoulos and Antoniou 2008), ordered logit/probit models Kubota 2007, 2008), impact score (Lee, Jin, and Ji 2009) and analytical hierarchy process (AHP; Mahmoud and Hine 2013).…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, researchers have employed different approaches to measure users'perceptions of service quality, as summarised by Mahmoud and Hine (2013). The first approach is the 'perception based measure' that primarily evaluates service quality through users' level of satisfaction against existing service levels.…”

Section: Introductionmentioning

confidence: 99%

“…The second approach is the 'weighted perception measure' that analyses the importance of different service attributes on users' overall perception of service quality (Mahmoud and Hine 2013). In this approach, a number of statistical techniques have been used by researchers, like structural equation modelling Mazzulla 2007, 2012;de Ona et al 2013), quadrant analysis (Martilla and James 1977), factor analysis (Tyrinopoulos and Antoniou 2008), ordered logit/probit models Kubota 2007, 2008), impact score (Lee, Jin, and Ji 2009) and analytical hierarchy process (AHP; Mahmoud and Hine 2013). While these approaches provide a good measure of users' perceptions of service quality, they do so with respect to the existing service quality and fail to provide a measure of future service quality.…”

Section: Introductionmentioning

confidence: 99%

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Determination of level-of-service scale values for quantitative bus transit service attributes based on user perception

Das

Pandit

2014

Transportmetrica A: Transport Science

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The need to assess service quality of existing transportation systems based on users'perceptions has received increased attention in recent years. In this context, researchers have identified level of service (LOS) as an effective tool to measure users' perceptions of service quality on a linguistic scale ranging from LOS A to LOS F which denote 'best' to 'worst' levels of service according to users' perceptions. However, contrary to the definition of LOS that requires it to be measured based on user perception, the existing LOS benchmarks available for public transportation are based on expert judgment. This research attempts to develop LOS benchmarks for bus transit services based on user perception using the 'Law of Successive Interval Scaling' which converts an ordered categorical scale into an interval scale. The results obtained through this analysis for the city of Kolkata, India, highlight the difference in LOS scale values between developed and developing nations and between expert opinion and user perception.

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“…The experts' knowledge was incorporated in the proposed model. Moataz and Julian [22] evaluated the user's perception of bus transit services by using a review. The gap in the perceptions held by the current and potential users was also measured.…”

Section: Review Of Optimization Techniquesmentioning

confidence: 99%

Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

Pandian¹,

Sundaram

Rajakarunakaran³

2016

PROMET

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Statistics reveals that the visual problems are the primereasons for a larger number of road accidents. The blind spotis the major problem related to vision. The aim of this studyis to develop a fuzzy-based multi criteria decision-makingmodel for optimizing the area of the blind spot in the frontand sides of a heavy transport vehicle. To achieve this, thestatistical tool ANOVA (Analysis of Variance) and multi criteriaoptimization techniques like TOPSIS (Technique for Orderof Preference by Similarity to Ideal Solution), FAHP (FuzzyAnalytical Hierarchy Process) and GRA (Grey RelationalAnalysis) were also used in this problem This paper consistsof three modules: first, the blind spots of the existing bodystructure dimension used in heavy vehicles were studiedand the optimal design parameters were determined by usingANOVA and TOPSIS methodologies; next, the weights ofthe design parameters were calculated using FAHP method.Finally, GRA-based Multi Criteria Decision Making (MCDM)approach has been used to rank the vehicle body structures.The proposed model has been implemented in a transportcorporation to compare four different types of body structuresand concluded that the body structure which was builtby an outsourced body builder is having a smaller area ofblind spot and optimal design parameters as well.

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Using AHP to measure the perception gap between current and potential users of bus services

Cited by 73 publications

References 28 publications

Using analytic network process to measure the determinants of low cost carriers purchase intentions: A comparison of potential and current customers

Using analytic network process to measure the determinants of low cost carriers purchase intentions: A comparison of potential and current customers

Determination of level-of-service scale values for quantitative bus transit service attributes based on user perception

Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

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